@article{SimonsLewinsohnBluethgenetal.2017,
  author    = {Simons, Nadja K. and Lewinsohn, Thomas and Bluethgen, Nico and Buscot, Francois and Boch, Steffen and Daniel, Rolf and Gossner, Martin M. and Jung, Kirsten and Kaiser, Kristin and M{\"u}ller, J{\"o}rg and Prati, Daniel and Renner, Swen C. and Socher, Stephanie A. and Sonnemann, Ilja and Weiner, Christiane N. and Werner, Michael and Wubet, Tesfaye and Wurst, Susanne and Weisser, Wolfgang W.},
  title     = {Contrasting effects of grassland management modes on species-abundance distributions of multiple groups},
  series = {Agriculture, ecosystems \& environment : an international journal for scientific research on the relationship of agriculture and food production to the biosphere},
  volume    = {237},
  journal   = {Agriculture, ecosystems \& environment : an international journal for scientific research on the relationship of agriculture and food production to the biosphere},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0167-8809},
  doi       = {10.1016/j.agee.2016.12.022},
  pages     = {143 -- 153},
  year      = {2017},
  abstract  = {Intensive land use is a major cause of biodiversity loss, but most studies comparing the response of multiple taxa rely on simple diversity measures while analyses of other community attributes are only recently gaining attention. Species-abundance distributions (SADs) are a community attribute that can be used to study changes in the overall abundance structure of species groups, and whether these changes are driven by abundant or rare species. We evaluated the effect of grassland management intensity for three land-use modes (fertilization, mowing, grazing) and their combination on species richness and SADs for three belowground (arbuscular mycorrhizal fungi, prokaryotes and insect larvae) and seven aboveground groups (vascular plants, bryophytes and lichens; arthropod herbivores; arthropod pollinators; bats and birds). Three descriptors of SADs were evaluated: general shape (abundance decay rate), proportion of rare species (rarity) and proportional abundance of the commonest species (dominance). Across groups, taxonomic richness was largely unaffected by land-use intensity and only decreased with increasing mowing intensity. Of the three SAD descriptors, abundance decay rate became steeper with increasing combined land-use intensity across groups. This reflected a decrease in rarity among plants, herbivores and vertebrates. Effects of fertilization on the three descriptors were similar to the combined land-use intensity effects. Mowing intensity only affected the SAD descriptors of insect larvae and vertebrates, while grazing intensity produced a range of effects on different descriptors in distinct groups. Overall, belowground groups had more even abundance distribtitions than aboveground groups. Strong differences among aboveground groups and between above- and belowground groups indicate that no single taxonomic group can serve as an indicator for effects in other groups. In the past, the use of SADs has been hampered by concerns over theoretical models underlying specific forms of SADs. Our study shows that SAD descriptors that are not connected to a particular model are suitable to assess the effect of land use on community structure.},
  language  = {en}
}
@article{FrielerSchaubergerArnethetal.2017,
  author    = {Frieler, Katja and Schauberger, Bernhard and Arneth, Almut and Balkovic, Juraj and Chryssanthacopoulos, James and Deryng, Delphine and Elliott, Joshua and Folberth, Christian and Khabarov, Nikolay and M{\"u}ller, Christoph and Olin, Stefan and Pugh, Thomas A. M. and Schaphoff, Sibyll and Schewe, Jacob and Schmid, Erwin and Warszawski, Lila and Levermann, Anders},
  title     = {Understanding the weather signal in national crop-yield variability},
  series = {Earths future},
  volume    = {5},
  journal   = {Earths future},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {2328-4277},
  doi       = {10.1002/2016EF000525},
  pages     = {605 -- 616},
  year      = {2017},
  abstract  = {Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50\% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50\% in seven countries, including the United States. The explained variance exceeds 50\% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.},
  language  = {en}
}